What Hides in Dimension X? A Quest for Visualizing Particle Swarms

  • Namrata Khemka
  • Christian Jacob
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5217)


The way we perform evolutionary experiments is all influenced by visualizing multi-dimensional solutions, analyzing the extent to which the search space is explored, displaying the gross population statistics, determining clustering and building blocks, and finding successful combinations of parameter values. Through visualization we can gain valuable insights to enhance our knowledge about particle swarm optimizers, in particular, and the search space that is being explored. In this paper, we focus on different visualization techniques for particle swarm systems. We investigate the advantages of a range of graphical data representation methods by example of the two- and four-dimensional sphere function, the two-dimensional simplified foxholes function, and a 56-dimensional real-world example in the context of muscle stimulus patterns.


Particle Swarm Optimization Search Space Particle Swarm Density Plot Benchmark Function 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Namrata Khemka
    • 1
  • Christian Jacob
    • 1
  1. 1.Evolutionary and Swarm Design Group, Dept. of Computer ScienceUniversity of CalgaryAlbertaCanada

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